Open-source alternatives to PolyFit

The Point Cloud Library is a collection of C++ algorithms designed for filtering, registering, and analyzing large-scale 3D spatial datasets. It provides a framework for 3D point cloud processing, incorporating tools for spatial data filtering and geometric feature estimation. The library includes specialized systems for aligning multiple spatial datasets into a single unified coordinate system and a rendering engine for the visual inspection and analysis of processed point cloud data. It also features tools for calculating spatial descriptors to identify structural patterns and shapes within

Point-e is a system for 3D model synthesis that generates three-dimensional point clouds from natural language descriptions and two-dimensional images. It utilizes diffusion models to synthesize these spatial representations based on text prompts or source images. The project includes specialized tools for refining these outputs, such as a point cloud upsampler to increase the density and resolution of low-resolution models. It also provides a mesh converter that uses distance function regression to transform raw point cloud data into structured 3D meshes. The broader capability surface cove

mmcv is a foundation library for computer vision based on PyTorch. It provides a comprehensive system for constructing convolutional neural networks, a toolkit for image and video preprocessing, and a collection of high-performance deep learning vision operators. The project is distinguished by its hardware-accelerated kernels for complex operations such as deformable convolutions and region pooling. It features a configuration-driven framework that allows for the dynamic instantiation of network layers and the registration of custom modules without modifying code. The library covers a broad

LIO-SAM is a lidar inertial SLAM framework and tightly-coupled sensor fusion pipeline. It functions as a factor graph optimization engine that combines lidar scans and inertial measurement unit data to build 3D point cloud maps and estimate robot trajectories. The system integrates global position factors to align local coordinates with real-world data. It employs loop closure detection to identify previously visited locations, creating constraints in the optimization graph to correct accumulated global drift. The framework covers lidar inertial odometry, point cloud processing, and trajecto

[paper](http://cseweb.ucsd.edu/~mil070/projects/AAAI2020/paper.pdf) [data](https://drive.google.com/drive/folders/1X143kUwtRtoPFxNRvUk9LuPlsf1lLKI7?usp=sharing)

LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation

Pure Julia reader of lasindex .lax files

Extends LasIO with Laszip integration

Deep Hough Voting for 3D Object Detection in Point Clouds

CloudCompare is a professional software application for processing and analyzing 3D point clouds and polygonal meshes. It functions as a 3D mesh analysis tool and a large dataset visualizer designed to display and manage millions of points in a 3D environment. The software provides specialized capabilities for point cloud comparison, utilizing an optimized octree structure to calculate spatial differences between two 3D datasets. This allows for the identification of variations and errors between point clouds or between a point cloud and a mesh. The system covers broad 3D data analysis areas

An Iterative Closest Point (ICP) library for 2D and 3D mapping in Robotics

Implementation for PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation (CVPR 2020)

Open3D is a 3D data processing library, visualization engine, and machine learning library. It provides a framework for manipulating point clouds and meshes through specialized algorithms designed for 3D data science workflows. The project includes a toolkit for 3D scene reconstruction to generate spatial models and align surfaces from raw data. It also functions as a GPU accelerated framework that offloads intensive spatial computations to the graphics processor to increase processing speed. The library covers a broad range of capabilities including physically based light simulations for vi

Remove then revert (IROS 2020)

ICRA2021 A low-cost SLAM system based on camera and Livox lidar.

The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.

Point cloud importer & renderer for Unity

LidarView performs real-time reception, recording, visualization and processing of 3D LiDAR data. This repository is a mirror of https://gitlab.kitware.com/LidarView/lidarview.

VeloView performs real-time visualization and easy processing of live captured 3D LiDAR data from Velodyne sensors (Alpha Prime™, Puck™, Ultra Puck™, Puck Hi-Res™, Alpha Puck™, Puck LITE™, HDL-32, HDL-64E). Runs on Windows, Linux and MacOS. This repository is a mirror of https://gitlab.kitware.com/LidarView/VeloView-Velodyne.

A lean C++ library for working with point cloud data

efficient tools for LiDAR processing

Chen-Hsuan Lin, Chen Kong, and Simon Lucey AAAI Conference on Artificial Intelligence (AAAI), 2018